动态超密集网络中的Markov预测切换

doi:10.11959/j.issn.1000-436x.2018225

通信学报 ›› 2018, Vol. 39 ›› Issue (10): 166-174.doi: 10.11959/j.issn.1000-436x.2018225

• 学术通信 • 上一篇

动态超密集网络中的Markov预测切换

孟庆民,赵媛媛,岳文静,邹玉龙,王小明

南京邮电大学通信与信息工程学院，江苏南京 210003

修回日期:2018-08-31 出版日期:2018-10-01 发布日期:2018-11-23
作者简介:孟庆民（1965-），男，江苏滨海人，博士，南京邮电大学副教授，主要研究方向为信号处理、网络智能、网络自动化、绿色通信、安全通信、移动边缘计算等。|赵媛媛（1992-），女，山东东营人，南京邮电大学硕士生，主要研究方向为无线资源管理。|岳文静（1982-），女，山西应县人，博士，南京邮电大学副教授，主要研究方向为协作通信、认知无线电等。|邹玉龙（1984-），男，江西新干人，博士，南京邮电大学教授，主要研究方向为认知无线电、信息安全等。|王小明（1986-），男，山东聊城人，博士，南京邮电大学讲师，主要研究方向为绿色通信、资源分配等。
基金资助:
国家自然科学基金资助项目(61522109);国家自然科学基金资助项目(61501253);国家自然科学基金资助项目(61801240);江苏省自然科学基金资助项目(15KJA510003);江苏省自然科学基金资助项目(BK20151506)

Markov prediction based handover in dynamic ultra dense network

Qingmin MENG,Yuanyuan ZHAO,Wenjing YUE,Yulong ZOU,Xiaoming WANG

College of Telecommunications ＆Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China

Revised:2018-08-31 Online:2018-10-01 Published:2018-11-23
Supported by:
The National Natural Science Foundation of China(61522109);The National Natural Science Foundation of China(61501253);The National Natural Science Foundation of China(61801240);The Natural Science Foundation of Jiangsu Province(15KJA510003);The Natural Science Foundation of Jiangsu Province(BK20151506)

摘要/Abstract

摘要：

针对超密集蜂窝网络中大规模机器类通信所涉及的通信与计算问题，提出了一种基于 Markov 预测的切换方案。首先考虑半结构化的中心控制的异构网络设计，该设计中含有密集部署的虚拟节点，以实现低成本和高效率的覆盖。该网络可以根据用户的移动性及网络通信量动态调整接入点。其次构建 Markov 模型，引入负载感知思想，通过权衡信号质量与小区负载，有效地预测用户的下一个最优接入点。仿真实验结果证明了该方案用于小区切换预测的可行性与有效性。

关键词: 超密集蜂窝网络, 大规模机器类通信, Markov模型, 负载感知, 切换

Abstract:

In order to solve the problem of the communication and computational problems of large-scale machine communication in an ultra-dense cellular network,a Markov prediction based handover scheme (MPHS) was proposed.Firstly,a kind of heterogeneous network design with semi-structure and central control was considered which contains the densely deployed virtual nodes and thus realized a low cost and efficient coverage.The network can dynamically adjust the access point according to the user's mobility and network traffic.Secondly,a Markov model was constructed,and the idea of load-aware was introduced.By weighing the signal quality and the cell load,the user's next optimal access point was effectively predicted.The simulation results show the feasibility and effectiveness of the proposed scheme for cell handover predicting.

Key words: ultra-dense cellular network, large-scale machine communication, Markov model, load-aware, handover

中图分类号:

TP393

孟庆民,赵媛媛,岳文静,邹玉龙,王小明. 动态超密集网络中的Markov预测切换[J]. 通信学报, 2018, 39(10): 166-174.

Qingmin MENG,Yuanyuan ZHAO,Wenjing YUE,Yulong ZOU,Xiaoming WANG. Markov prediction based handover in dynamic ultra dense network[J]. Journal on Communications, 2018, 39(10): 166-174.

图/表 11

图1

图2

图3

表1

系统仿真参数说明"

参数	说明	值
R	宏小区半径	600 m
D	宏基站到虚拟基站的距离	$\frac{600}{\sqrt{3}}$
$P_{M}^{t x}$	宏基站的信号发射功率	46 dBm
$P_{V}^{t x}$	虚拟基站的信号发射功率	24 dBm
μ_M	宏基站路径损耗系数	4.5
μ_N	虚拟基站路径损耗系数	2.5
DSF	阴影方差	4 dB
f_c	系统载频	3.65 GHz
N₀	噪声功率谱密度	-174 dBm/Hz
B_a	含12个子载波的子信道的有效带宽	72 kHz
Nch	子信道总数	32
ω	簇用户的移动方向	$\frac{π}{6}$

表1

图4

表2

表3

表4

图5

图6

图7

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基站	V₁	V₂	V₃	V₄	V₅	V₆	V₇	V₈	V₉	V₁₀	V₁₁	V₁₂	M
ρ_n	1.0	0.3	1.0	0.3	1.0	0.3	1.0	0.3	1.0	0.3	1.0	0.3	1.0

基站	V₁	V₂	V₃	V₄	V₅	V₆	V₇	V₈	V₉	V₁₀	V₁₁	V₁₂	M
ρ_n	0.7	1.0	0.5	0.3	1.0	0.5	0.7	0.3	0.7	1.0	0.5	0.7	1.0

负载配置	用户所选择基站序列
不考虑负载，即ρ_n=1	V₈→V₉→V₈→V₉→V₁₀→V₁₁→V₁₂→V₁
ρ_n如表2所示	V₉→V₁₁→V₁
ρ_n如表3所示	V₁₀→V₂

动态超密集网络中的Markov预测切换

Markov prediction based handover in dynamic ultra dense network

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